P.051 Epilepsy Absence of children, A Guinean cohort of 69 cases
Bibliographic record
Abstract
Background: Absence epilepsy is a common epilepsy syndrome in children. This can have a negative impact on the cognitive abilities of preschool and school-age children. The objective was to study in the Guinean context, the epidemiological, clinical, electrophysiological, therapeutic and evolutionary aspects of this syndrome. Methods: The study included all children diagnosed with absence epilepsy based on evidence obtained from history, clinical, and electroencephalogram. Results: The cohort was made up of 41 girls and 28 boys with a sex ratio (F/M) equal to 1.46. The mean age was 8 ± 2 years with extremes of 2 and 14 years. The simple absences were observed in 42.02% of cases. The components : tonic was associated in 11.59%, clonic in 10.14%, atonic in 13.04%, automatisms in 15.94% and vegetative in 7.25%. EEG was typical in 75.36%. As monotherapy, sodium valproate was used in 92.75% and ethosuximide in 2.9%. The evolution was marked by a remission of seizures in 85.51%. During follow-up, the appearance of tonic-clonic convulsions was noted in 4.3%, myoclonus in 2.9%, a combination of myoclonus and tonic-clonic convulsions noted in 4.3%. Conclusions: Effective and efficient collaboration between stakeholders is essential for the best overall management of this syndrome with serious cognitive repercussions in children.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".